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Sensing as a Service Model forSmart Cities Supported byInternet of Things

Jos Rodrigues Torres Neto

Perera C, Zaslavsky A, Christen P, Georgakopoulos D. Sensing as a ServiceModel for Smart Cities Supported by Internet of Things. Trans. Emerging Tel.Tech. 2014; 00: 112.


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INTRODUCTION

The Internet of ThingsIoTallows people and

things to be connected anytime, anyplace, with

anything and anyone, ideally using any

path/network and any service.

The Smart Cities SC are originated to solve the

problems in modern cities using information and

communication technologies (ICT).


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INTRODUCTION


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INTRODUCTION

THIS PAPER IS ORGANISED AS FOLLOWS:

Section 1: Introduction

Section 2: Review the trends of everything as a service

Section 3: The sensing as a service model

Section 4: Explain the sensing as a service model using a futuristic scenario.

Section 5: Discuss several use case scenarios that highlight the different aspectsof the sensing as a service model.

Section 6: Discuss the advantages in sensing as a service model

Section 7: Highlight some of the major open challenges and issues related tosensing as a service model.

Section 8: Present the concluding remarks.


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THE TRENDS: EVERYTHING AS ASERVICE- (XaaS)

Is to concentrate resources such as hardware and software

into few physical locations and offer those resources as

services to a large number of consumers who are located in

many different geographical locations around the globe over

the Internet in an efficient manner. Ex: infrastructure-as-a-service, platform-as-a-service and software-as-a-service;

One major reason behind the success of XaaS model is the

cost effectiveness.(pay as you go);

Cloud computing service models provide many other

benefits such as business agility, scalability and elasticity,

reliability, green initiatives, less maintenance work including

backup and disaster recovery.


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SMART CITY - SC

Smart City initiatives have become another trend during the past

decade.

Leading projects: IBM Smart Planet and Smart Cities, OracleiGovernment, Amsterdam Smart City, Dubai Smart City, European

Smart Cities and SC Future;

XaaS and

Cloud$37,8bi

2010

$121,1bi2015

$1tri2016

Smart City

Expected growth

THE TRENDS: EVERYTHING AS ASERVICE- (XaaS)


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SENSING AS A SERVICE MODEL Sensors and Sensor Owners (A sensor is a device that detects, measures or

sense a physical phenomenon such as humidity, temperature and so on).

- Categories of Sensors:a) Personal and Households

All personal items, e.g. mobiles phones, laptops, food items and household items.

b) Private organisations/placesAll items own by private organisations.

c) Public organisations/places

Public infrastructure such as bridges, roads and parks.d) Commercial Sensor Data Providers

Business entities who deploy and manage sensors by themselves by keeping ownership.

Sensor Publishers (Detect available sensors, communicate with the sensorowners and obtain permission to publish the sensors in the cloud.)

Extended Service Providers (The most intelligent among all the four layers.The services provided by ESPs can be varied widely from one provider toanother.)

Sensor Data Consumers (Some of the major sensor data consumers would begovernments, business organisations, academic institutions and scientific research

communities).


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SENSING AS A SERVICE MODEL


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SENSING AS A SERVICE IN ACTION Three different use case scenarios that explain different aspects

of the sensing as a service model:i. Waste management;

Waste management consists of different processes such as collection, transport,processing, disposal, managing and monitoring of waste materials. (money, timeand labour). In a modern Smart City, there are several parties who are interested inwaste management (e.g. city council, recycling companies, manufacturing plantsand authorities related to health and safety).

ii. Smart Agriculture;Agriculture is an importation part of SC as it contributes to the food supply chainthat facilitates a large number of communities concentrated into cities.

E.g. Phenonet project: to monitor plant growth and performance information and

climate conditions.

iii. Environmental Management.Most of the sensors used in environmental monitoring are commonly used in otherdomains such as climate, wild fire detection and structural health monitoring


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ADVANTAGES AND BENEFITS Built-in cloud computing: it inherits all the benefits of the fundamental

cloud computing models(e.g. infrastructure-as-a-service, platform-as-a-service and software-as-a-service).

Participatory sensing: The workload is distributed among different players

in the model.

Sharing and reusing: Sensing as a service is a model that stimulates by

concept of sharing. In simple terms, if someone has already deployed the

sensors, others can have access to them by paying a fee to the sensor owner.

Reduction of data acquisition cost: Because of the shared and collaborative

nature, data acquisition cost will be reduced significantly.

Collect data previously unavailable: This model allows to collect sensor

data, which is impossible to collect using traditional non-collaborative

methods.


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Innovations: Because of a reduction in sensor data acquisition cost, largernumber of interest groups will be able to access to them.

Applications: Easily accessible sensor data allows government authorities,academia, research institutions and businesses to address differentchallenges in SC such as traffic; energy; water; education; andunemployment, health, and crime management.

Real-time data for decision making and policy making: This model enablescollecting sensor data in real time, from a variety of different domains,which facilitates the decision making processes.

Direct and indirect benefits: The sensing as a service model creates a win-

win situation for all the parties involved.

Privacy preservation: This model provide complete control of the privacyof sensor owners in their own hands. The final decision of whether to

publish their sensors or not is taken by the sensor owners.

ADVANTAGES AND BENEFITS


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OPEN CHALLENGES

Technological:1. Architectural designs, sensor configuration, data fusing/filtering,

processing/storage, infrastructure and energy consumption

2. Standardisation, accuracy, and security and privacy.

Economical1. Innovation, entrepreneurship and entry barriers

2. Sustainability, licensing, business practices and credibility

Social1. Trust, social acceptance, change management, awareness

2. Security and privacy, safety, accessibility, usability and legalterms.


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CONCLUSIONS

This paper provides a comprehensive overview of the

sensing as a service model and its applicability towards SC in

the IoT paradigm. We discussed the model from three

different perspectives including technological, economical

and social. We examined how the sensing as a service can be

a sustainable, scalable and powerful model.

This model will create an unprecedented amount of

opportunities to build innovative value added solutions that

makes the decision making process efficient and effective in

IoT paradigm.

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